Relevant bibliographies by topics / Thermal time

Academic literature on the topic 'Thermal time'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 March 2023

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Journal articles on the topic "Thermal time"

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Skach, Matt, Manish Arora, Chang-Hong Hsu, Qi Li, Dean Tullsen, Lingjia Tang, and Jason Mars. "Thermal time shifting." ACM SIGARCH Computer Architecture News 43, no. 3S (January 4, 2016): 439–49. http://dx.doi.org/10.1145/2872887.2749474.

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Shimokusu, Trevor J., Qing Zhu, Natan Rivera, and Geoff Wehmeyer. "Time-periodic thermal rectification in heterojunction thermal diodes." International Journal of Heat and Mass Transfer 182 (January 2022): 122035. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2021.122035.

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Arora, D., M. Skliar, and R. B. Roemer. "Minimum-Time Thermal Dose Control of Thermal Therapies." IEEE Transactions on Biomedical Engineering 52, no. 2 (February 2005): 191–200. http://dx.doi.org/10.1109/tbme.2004.840471.

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del Monte, J. P., P. L. Aguado, and A. M. Tarquis. "Thermal time model ofSolanum sarrachoidesgermination." Seed Science Research 24, no. 4 (September 16, 2014): 321–30. http://dx.doi.org/10.1017/s0960258514000221.

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AbstractA population-based modelling approach was used to predict the occurrence of germination inSolanum sarrachoides(SOLSA) for different treatments. Seeds collected in Toledo (Spain) were exposed to constant temperatures, to temperatures alternating between 10 and 30°C and to gibberellins (GAs; 0, 50, 100, 150 and 1000 ppm) during a 24-h imbibition period. The following parameters were measured: base temperature (Tb), mean thermal time (θT(50)) and the standard deviation of thermal time (σθT). The SOLSA seeds only germinated at constant temperatures when the highest GA concentration was applied. The thermal model suggests that the induction and loss of physiological dormancy following seed dispersal is achieved when temperatures vary and when a mean thermal time of 66 growing degree-days (d°C) and aTbvalue of 16°C are achieved when no GA treatment was added. The concentration of GA applied under conditions of alternating temperatures has an additive effect, reducing θT(50) up to threefold, from basal level (66 d°C) to 19.40 d°C, when the 1000 ppm GA treatment was applied. In this last case, the germination was accelerated by reducingTbto 14°C. A 5–10°C change in temperature and a range of average temperatures of 20–27.5°C promoted the germination of SOLSA seeds to the greatest extent in the absence of GA. However, these conditions are not frequently encountered in the irrigated areas of the studied region; this finding could explain the limited ability of SOLSA to expand its range within this area.
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Esman, R. D., and D. L. Rode. "Semiconductor‐laser thermal time constant." Journal of Applied Physics 59, no. 2 (January 15, 1986): 407–9. http://dx.doi.org/10.1063/1.336644.

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TRUDGILL, D. L., A. HONEK, D. LI, and N. M. STRAALEN. "Thermal time - concepts and utility." Annals of Applied Biology 146, no. 1 (January 2005): 1–14. http://dx.doi.org/10.1111/j.1744-7348.2005.04088.x.

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Hüttner, Bernd. "Is thermal conductivity time-dependent?" physica status solidi (b) 245, no. 12 (December 2008): 2786–90. http://dx.doi.org/10.1002/pssb.200844182.

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Borghi, Claudio. "Physical Time and Thermal Clocks." Foundations of Physics 46, no. 10 (July 6, 2016): 1374–79. http://dx.doi.org/10.1007/s10701-016-0030-y.

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Marshalov, Е. D., A. N. Nikonorov, and I. K. Muravyov. "Determination of thermal response time of thermal resistance transducers." Vestnik IGEU, no. 3 (2017): 54–59. http://dx.doi.org/10.17588/2072-2672.2017.3.054-059.

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Khafizov, Marat, and David H. Hurley. "Measurement of thermal transport using time-resolved thermal wave microscopy." Journal of Applied Physics 110, no. 8 (October 15, 2011): 083525. http://dx.doi.org/10.1063/1.3653829.

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Dissertations / Theses on the topic "Thermal time"

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Feldgoise, Jeffrey. "Thermal design through space and time." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/65983.

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Thesis (M. Arch.)--Massachusetts Institute of Technology, Dept. of Architecture, 1997.
Includes bibliographical references (p. 89-90).
One of the primary roles of architecture is to control the environment at the service of a building's inhabitants. Thermal qualities are a significant factor in the overall experience one has inside and outside a building. However, thermal issues are not often considered within the context of the architectural design process, resulting in buildings that are not responsive to thermal concerns. Heat has the potential to influence the form of architectural space. The methods by which architects can use thermal energy as a formative element in design is open to further exploration. In this thesis, I explore new methods for architects to describe thermal intentions and visualize thermal qualities of design proposals. Beyond the economic issue of energy conservation, the thermal qualities of building spaces affect the quality of human inhabitation. The capability to describe and visualize heat would allow architects to adjust the building's thermal characteristics to modify a person's experience of the place. With a more complete understanding of thermal qualities of their building proposals, architects would be able to design for the complete gamut of thermal sensations that humans can experience. What is needed is a working vocabulary that describes the range of thermal conditions possible in buildings. In this work, I describe a vocabulary for a building's thermal qualities using four sets of measurable, opposing terms: open versus protected, bright versus dim, warm versus cool, and active versus still. Next, I then articulate the thermal qualities of a co-housing project to create a thermal experience that enhances the community aspects of co-housing. Using a variety of visualization techniques, I verify that the design proposal is achieving the intended thermal goals. Using the knowledge gained from this and future thermal design exercises, we can begin to reflect on the general relationships between thermal phenomena and physical building forms, learning about the thermal qualities of architecture.
Jeffrey Feldgoise.
M.Arch.
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Alshatshati, Salahaldin Faraj. "Estimating Envelope Thermal Characteristics from Single Point in Time Thermal Images." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512648630005333.

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Michiorri, Andrea. "Power system real-time thermal rating estimation." Thesis, Durham University, 2010. http://etheses.dur.ac.uk/469/.

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This Thesis describes the development and testing of a real-time rating estimation algorithm developed at Durham University within the framework of the partially Government-funded research and development project “Active network management based on component thermal properties”, involving Durham University, ScottishPower EnergyNetworks, AREVA-T&D, PB Power and Imass. The concept of real time ratings is based on the observation that power system component current carrying capacity is strongly influenced by variable environmental parameters such as air temperature or wind speed. On the contrary, the current operating practice consists of using static component ratings based on conservative assumptions. Therefore, the adoption of real-time ratings would allow latent network capacity to be unlocked with positive outcomes in a number of aspects of distribution network operation. This research is mainly focused on facilitating renewable energy connection to the distribution level, since thermal overloads are the main cause of constraints for connections at the medium and high voltage levels. Additionally its application is expected to facilitate network operation in case of thermal problems created by load growth, delaying and optimizing network reinforcements. The work aims at providing a solution to part of the problems inherent in the development of a real-time rating system, such as reducing measurements points, data uncertainty and communication failure. An extensive validation allowed a quantification of the performance of the algorithm developed, building the necessary confidence for a practical application of the system developed.
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Gaffney, Eamonn Andrew. "Aspects of imaginary time thermal field theory." Thesis, University of Cambridge, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627526.

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LeVett, Marshall Allan. "Parallel Time-Marching for Fluid-Thermal-Structural Interactions." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1452178897.

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Babich, Francesco. "Thermal comfort in non-uniform environments : real-time coupled CFD and human thermal regulation modelling." Thesis, Loughborough University, 2017. https://dspace.lboro.ac.uk/2134/32835.

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Energy consumption in buildings contributes more greenhouse gas emissions than either the industrial or transportation sectors, primarily due to space cooling and heating energy use, driven by the basic human need for thermal comfort and good indoor air quality. In recent years, there has been a proliferation of air conditioning in both residential and commercial buildings especially in the developing economic areas of the world, and, due to the warming climate and the growing disposable income in several densely populated developing countries, the energy demand for space cooling is dramatically increasing. Although several previous studies focused on thermal comfort, there are only a few works on asymmetrical environments or transient conditions, such as those expected when mixed mode ventilation or other low energy techniques such as elevated air movement generated by ceiling fans are adopted in the residential sector. Moreover, even fewer studies addressed the accuracy of computer predictions of human thermal comfort in non-uniform environmental conditions. However, focusing on non-uniform thermal environments is important because the space conditioning systems that generate them are often likely to be less energy consuming than those which provide more homogeneous conditions. This is due to the fact that these less energy-intensive space conditioning systems tend to condition the occupants, and not the entire room. The aim of this research was to investigate human thermal comfort in non-uniform transient environmental conditions, focusing in particular on the capability of predicting human thermal comfort in such conditions in residential buildings. Furthermore, this research investigated the energy savings that can be achieved in residential buildings when the same level of thermal comfort is delivered using less conventional, but lower-energy, approaches. In this research, a combination of computer based modelling, experimental work in controlled environments, and data from field studies was used. Computer modelling comprised CFD coupled with a model of human thermal physiology and human thermal comfort, and dynamic thermal modelling. In the experimental work, environmental chambers were used to collect data to validate the coupled CFD model. The data from field studies on real domestic buildings in India and in the UK was used to identify the most relevant configurations to be modelled using the coupled system. This research led to three main conclusions concerning thermal comfort in non-uniform environments: (i) the coupled model is able to predict human thermal comfort in complex non-uniform indoor configurations, as long as the environment around the human body is accurately modelled in CFD, and is superior to the traditional PMV model as both temporal and spatial variation and non-uniform conditions can be taken into account; (ii) dynamic thermal simulation completed using a dynamic cooling set-point showed that the energy demand for space cooling can be reduced by as much as 90% in mixed mode buildings by using ceiling fans, without jeopardising occupants' thermal comfort; and (iii) the accurate and validated transient three-dimensional CFD model of a typical Indian ceiling fan developed in this research can be used for any study that requires the air flow generated by a ceiling fan to be modelled in CFD.
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Acomb, Simon. "Applications of nonlinear dynamics to time dependent thermal convection." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305477.

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Cosma, Andrei Claudiu. "Real-Time Individual Thermal Preferences Prediction Using Visual Sensors." Thesis, The George Washington University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=13422566.

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The thermal comfort of a building’s occupants is an important aspect of building design. Providing an increased level of thermal comfort is critical given that humans spend the majority of the day indoors, and that their well-being, productivity, and comfort depend on the quality of these environments. In today’s world, Heating, Ventilation, and Air Conditioning (HVAC) systems deliver heated or cooled air based on a fixed operating point or target temperature; individuals or building managers are able to adjust this operating point through human communication of dissatisfaction. Currently, there is a lack in automatic detection of an individual’s thermal preferences in real-time, and the integration of these measurements in an HVAC system controller.

To achieve this, a non-invasive approach to automatically predict personal thermal comfort and the mean time to discomfort in real-time is proposed and studied in this thesis. The goal of this research is to explore the consequences of human body thermoregulation on skin temperature and tone as a means to predict thermal comfort. For this reason, the temperature information extracted from multiple local body parts, and the skin tone information extracted from the face will be investigated as a means to model individual thermal preferences.

In a first study, we proposed a real-time system for individual thermal preferences prediction in transient conditions using temperature values from multiple local body parts. The proposed solution consists of a novel visual sensing platform, which we called RGB-DT, that fused information from three sensors: a color camera, a depth sensor, and a thermographic camera. This platform was used to extract skin and clothing temperature from multiple local body parts in real-time. Using this method, personal thermal comfort was predicted with more than 80% accuracy, while mean time to warm discomfort was predicted with more than 85% accuracy.

In a second study, we introduced a new visual sensing platform and method that uses a single thermal image of the occupant to predict personal thermal comfort. We focused on close-up images of the occupant’s face to extract fine-grained details of the skin temperature. We extracted manually selected features, as well as a set of automated features. Results showed that the automated features outperformed the manual features in all the tests that were run, and that these features predicted personal thermal comfort with more than 76% accuracy.

The last proposed study analyzed the thermoregulation activity at the face level to predict skin temperature in the context of thermal comfort assessment. This solution uses a single color camera to model thermoregulation based on the side effects of the vasodilatation and vasoconstriction. To achieve this, new methods to isolate skin tone response to an individual’s thermal regulation were explored. The relation between the extracted skin tone measurement and the skin temperature was analyzed using a regression model.

Our experiments showed that a thermal model generated using noninvasive and contactless visual sensors could be used to accurately predict individual thermal preferences in real-time. Therefore, instantaneous feedback with respect to the occupants' thermal comfort can be provided to the HVAC system controller to adjust the room temperature.

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Mackwood, Andrew. "Numerical simulations of thermal processes and welding." Thesis, University of Essex, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272572.

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Huang, Huang. "Power and Thermal Aware Scheduling for Real-time Computing Systems." FIU Digital Commons, 2012. http://digitalcommons.fiu.edu/etd/610.

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Over the past few decades, we have been enjoying tremendous benefits thanks to the revolutionary advancement of computing systems, driven mainly by the remarkable semiconductor technology scaling and the increasingly complicated processor architecture. However, the exponentially increased transistor density has directly led to exponentially increased power consumption and dramatically elevated system temperature, which not only adversely impacts the system's cost, performance and reliability, but also increases the leakage and thus the overall power consumption. Today, the power and thermal issues have posed enormous challenges and threaten to slow down the continuous evolvement of computer technology. Effective power/thermal-aware design techniques are urgently demanded, at all design abstraction levels, from the circuit-level, the logic-level, to the architectural-level and the system-level. In this dissertation, we present our research efforts to employ real-time scheduling techniques to solve the resource-constrained power/thermal-aware, design-optimization problems. In our research, we developed a set of simple yet accurate system-level models to capture the processor's thermal dynamic as well as the interdependency of leakage power consumption, temperature, and supply voltage. Based on these models, we investigated the fundamental principles in power/thermal-aware scheduling, and developed real-time scheduling techniques targeting at a variety of design objectives, including peak temperature minimization, overall energy reduction, and performance maximization. The novelty of this work is that we integrate the cutting-edge research on power and thermal at the circuit and architectural-level into a set of accurate yet simplified system-level models, and are able to conduct system-level analysis and design based on these models. The theoretical study in this work serves as a solid foundation for the guidance of the power/thermal-aware scheduling algorithms development in practical computing systems.
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Books on the topic "Thermal time"

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Choy, Vanessa W. S. Real-time online fuzzy logic controller for laser interstitial thermal therapy. Ottawa: National Library of Canada, 2003.

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B, Lakshminarayana, and United States. National Aeronautics and Space Administration., eds. Dynamic and thermal turbulent time scale modelling for homogeneous shear flows. [Washington, DC]: National Aeronautics and Space Administration, 1994.

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S̆imunić, Dina. Thermal and stimutalting effects of time-varying magnetic fields during MRI. Aachen: Shaker, 1995.

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Beggs, C. B. The use of ice thermal storage with real time electricity pricing. Leicester: De Montfort University, 1995.

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Wang, Weixun. Dynamic Reconfiguration in Real-Time Systems: Energy, Performance, and Thermal Perspectives. New York, NY: Springer New York, 2013.

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B, Lakshminarayana, and United States. National Aeronautics and Space Administration., eds. Dynamic and thermal turbulent time scale modelling for homogeneous shear flows. [Washington, DC]: National Aeronautics and Space Administration, 1994.

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Lunardini, Virgil J. Permafrost formation time. [Hanover, N.H]: US Army Corps of Engineers, Cold Regions Research & Engineering Laboratory, 1995.

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Wheatley, C. J. CHARM, a model for aerosol behavior in time varying thermal-hydraulic conditions. Washington, DC: Division of Systems Research, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1988.

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Simpson, William Turner. Heat sterilization time of Ponderosa pine and Douglas-fir boards and square timbers. Madison, Wis: U.S. Dept. of Agriculture, Forest Service, Forest Products Laboratory, 2003.

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C, Öztürk Mehmet, Roozeboom Fred, Electrochemical Society Electronics Division, Electrochemical Society. Dielectric Science and Technology Division., Electrochemical Society. High Temperature Materials Division., and Electrochemical Society Meeting, eds. Advanced short-time thermal processing for Si-based CMOS devices II: Proceedings of the international symposium. Pennington, NJ: Electrochemical Society, 2004.

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Book chapters on the topic "Thermal time"

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Gooch, Jan W. "Thermal Death Time." In Encyclopedic Dictionary of Polymers, 928. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_14954.

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Bulgariu, Emilian. "Backward in Time Problems." In Encyclopedia of Thermal Stresses, 337–44. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-2739-7_244.

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Naso, Maria Grazia. "Asymptotic Behavior in Time." In Encyclopedia of Thermal Stresses, 251–57. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-2739-7_531.

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Laine, Mikko, and Aleksi Vuorinen. "Real-Time Observables." In Basics of Thermal Field Theory, 147–96. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31933-9_8.

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Zampoli, Vittorio. "Asymptotic Partition Backward in Time." In Encyclopedia of Thermal Stresses, 263–71. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-2739-7_532.

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Tibullo, Vincenzo. "Spatial Behavior Backward in Time." In Encyclopedia of Thermal Stresses, 4505–11. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-2739-7_540.

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Masterson, Robert E. "Time-Dependent Nuclear Heat Transfer." In Nuclear Reactor Thermal Hydraulics, 461–84. Boca Raton : CRC Press, [2019]: CRC Press, 2019. http://dx.doi.org/10.1201/b22067-12.

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Ehrenstein, Gottfried W., Gabriela Riedel, and Pia Trawiel. "Oxidative Induction Time/Temperature (OIT)." In Thermal Analysis of Plastics, 111–38. München: Carl Hanser Verlag GmbH & Co. KG, 2004. http://dx.doi.org/10.3139/9783446434141.002.

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Helerea, Elena, and Alfons Ifrim. "Thermal Life-Time for Bakelites." In Brittle Matrix Composites 3, 585–92. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3646-4_62.

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Favro, L. D., H. J. Jin, P. K. Kuo, R. L. Thomas, and Y. X. Wang. "Real Time Thermal Wave Tomography." In Photoacoustic and Photothermal Phenomena III, 519–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-540-47269-8_130.

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Conference papers on the topic "Thermal time"

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Skach, Matt, Manish Arora, Chang-Hong Hsu, Qi Li, Dean Tullsen, Lingjia Tang, and Jason Mars. "Thermal time shifting." In ISCA '15: The 42nd Annual International Symposium on Computer Architecture. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2749469.2749474.

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Zhang, Shu, Xiaohong Liu, Nishi Ahuja, Yu Han, Liyin Liu, Shuiwang Liu, and Yeye Shen. "On demand cooling with real time thermal information." In 2015 31st Thermal Measurement, Modeling & Management Symposium (SEMI-THERM). IEEE, 2015. http://dx.doi.org/10.1109/semi-therm.2015.7100152.

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Ahmadi, Mehran, Mohammad Fakoor Pakdaman, and Majid Bahrami. "Analytical investigation of thermal contact resistance (TCR) behavior under time-dependent thermal load." In 2016 32nd Thermal Measurement, Modeling & Management Symposium (SEMI-THERM). IEEE, 2016. http://dx.doi.org/10.1109/semi-therm.2016.7458440.

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Steinmetz, Jon, Subhash C. Patel, and Stanley E. Zocholl. "Stator thermal time constant." In 2013 IEEE/IAS 49th Industrial & Commercial Power Systems Technical Conference (I&CPS). IEEE, 2013. http://dx.doi.org/10.1109/icps.2013.6547350.

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Boglietti, Aldo, Enrico Carpaneto, Marco Cossale, and Alex Lucco Borlera. "Stator thermal model for short-time thermal transients." In 2014 International Conference on Electrical Machines (ICEM). IEEE, 2014. http://dx.doi.org/10.1109/icelmach.2014.6960367.

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Kendig, Dustin, Eiji Yagyu, Kazuaki Yazawa, and Ali Shakouri. "Submicron local and time-dependent thermal resistance characterization of GaN HEMTs." In 2018 34th Thermal Measurement, Modeling & Management Symposium (SEMI-THERM). IEEE, 2018. http://dx.doi.org/10.1109/semi-therm.2018.8357369.

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Socolinsky, D. A., and A. Selinger. "Thermal face recognition over time." In Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. IEEE, 2004. http://dx.doi.org/10.1109/icpr.2004.1333735.

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Xuefei Han and Yogendra Joshi. "Energy reduction in server cooling via real time thermal control." In 2012 IEEE/CPMT 28th Semiconductor Thermal Measurement & Management Symposium (SEMI-THERM). IEEE, 2012. http://dx.doi.org/10.1109/stherm.2012.6188829.

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Miskell, Kyle, Andrew N. Lemmon, and H. Bryan Owings. "On the Parametric Thermal Analysis of Emissive Heat Loss in Multi-Layer Vacuum-Enclosed Timing Systems." In Precise Time and Time Interval Systems and Applications Meeting. Institute of Navigation, 2016. http://dx.doi.org/10.33012/2016.13159.

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Chauhan, Anjali, Bahgat Sammakia, and Kanad Ghose. "Transient power analysis to estimate the thermal time lag of a microprocessor hot spot." In 2015 31st Thermal Measurement, Modeling & Management Symposium (SEMI-THERM). IEEE, 2015. http://dx.doi.org/10.1109/semi-therm.2015.7100143.

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Reports on the topic "Thermal time"

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Socolinsky, Diego A., and Andrea Selinger. Thermal Face Recognition Over Time. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada444423.

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Christofferson, James, Daryoosh Vashaee, Ali Shakouri, and Philip Melese. Real Time Sub-Micron Thermal Imaging Using Thermoreflectance. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada461268.

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Wiedmeier, Alisha, Ngozi Ezenagu, Vina Onyango-Robshaw, Alynie Walter, Viviana Montenegro Cortez, Rachel DuBose, Brittany Craig, et al. Balloon borne stratospheric night-time and day-time thermal wake differential temperature measurements. Ames (Iowa): Iowa State University. Library. Digital Press, January 2018. http://dx.doi.org/10.31274/ahac.11070.

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Hsu, P., G. Hust, M. McClelland, and M. Gresshoff. One-Dimensional Time to Explosion (Thermal Sensitivity) of ANPZ. Office of Scientific and Technical Information (OSTI), November 2014. http://dx.doi.org/10.2172/1183545.

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Hsu, P. C., G. Hust, M. McClelland, and M. Gressholf. One-Dimensional Time to Explosion (Thermal Sensitivity) of DMDNP. Office of Scientific and Technical Information (OSTI), November 2014. http://dx.doi.org/10.2172/1183560.

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Wang, Xinwei, and David H. Hurley. In-pile Thermal Conductivity Characterization with Time Resolved Raman. Office of Scientific and Technical Information (OSTI), March 2018. http://dx.doi.org/10.2172/1427519.

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COMPTON, J. A. Time and Temperature Test Results for PFP Thermal Stabilization Furnaces. Office of Scientific and Technical Information (OSTI), August 2000. http://dx.doi.org/10.2172/804505.

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Cahill, David G. Thermal Conductivity of Novel Thermoelectric and Nanostructured Functional Materials by Time-Domain Thermoreflectance. Fort Belvoir, VA: Defense Technical Information Center, June 2010. http://dx.doi.org/10.21236/ada523273.

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Daryanian, B., R. D. Tabors, and R. E. Bohn. Automatic control of electric thermal storage (heat) under real-time pricing. Final report. Office of Scientific and Technical Information (OSTI), January 1995. http://dx.doi.org/10.2172/26391.

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10

Dennis H. LeMieux. On-Line Thermal Barrier Coating Monitoring for Real-Time Failure Protection and Life Maximization. Office of Scientific and Technical Information (OSTI), October 2005. http://dx.doi.org/10.2172/883320.

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